Imperial College London

ProfessorMarjo-RiittaJarvelin

Faculty of MedicineSchool of Public Health

Chair in Lifecourse Epidemiology
 
 
 
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+44 (0)20 7594 3345m.jarvelin

 
 
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156Norfolk PlaceSt Mary's Campus

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Summary

 

Publications

Publication Type
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976 results found

Makinen V-P, Karsikas M, Kettunen J, Lehtimaki T, Kahonen M, Viikari J, Perola M, Salomaa V, Jarvelin M-R, Raitakari OT, Ala-Korpela Met al., 2022, Longitudinal profiling of metabolic ageing trends in two population cohorts of young adults, INTERNATIONAL JOURNAL OF EPIDEMIOLOGY, Vol: 51, Pages: 1970-1983, ISSN: 0300-5771

Journal article

Jarvelin M-R, 2022, DNA methylation signature of chronic low-gradeinflammation and its role in cardio-respiratorydiseases, Nature Communications, Vol: 13, ISSN: 2041-1723

We performed a multi-ethnic Epigenome Wide Association study on 22,774 individuals to describe the DNA methylation signature of chronic low-grade inflammation as measured by C-Reactive protein (CRP). We find 1,511 independent differentially methylated loci associated with CRP. These CpG sites show correlation structures across chromosomes, and are primarily situated in euchromatin, depleted in CpG islands. These genomic loci are predominantly situated in transcription factor binding sites and genomic enhancer regions. Mendelian randomization analysis suggests altered CpG methylation is a consequence of increased blood CRP levels. Mediation analysis reveals obesity and smoking as important underlying driving factors for changed CpG methylation. Finally, we find that an activated CpG signature significantly increases the risk for cardiometabolic diseases and COPD.

Journal article

Said S, Karhunen V, vosa U, ligthart S, Bodinier B, Koskeridis F, welsh P, Alizadeh B, Daniel C, sattar N, Chadeau M, evalgelou E, Jarvelin M-R, Elliott P, Tzoulaki I, Dehghan Aet al., 2022, Genetic analysis of over half a million people characterises C-reactive protein loci, Nature Communications, Vol: 13, ISSN: 2041-1723

Chronic low-grade inflammation is linked to a multitude of chronic diseases. We report the largest genome-wide association study (GWAS) on C-reactive protein (CRP), a marker of systemic inflammation, in UK Biobank participants (N = 427,367, European descent) and the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium (total N = 575,531 European descent). We identify 266 independent loci, of which 211 are not previously reported. Gene-set analysis highlighted 42 gene sets associated with CRP levels (p ≤ 3.2 ×10−6) and tissue expression analysis indicated a strong association of CRP related genes with liver and whole blood gene expression. Phenome-wide association study identified 27 clinical outcomes associated with genetically determined CRP and subsequent Mendelian randomisation analyses supported a causal association with schizophrenia, chronic airway obstruction and prostate cancer. Our findings identified genetic loci and functional properties of chronic low-grade inflammation and provided evidence for causal associations with a range of diseases.

Journal article

Ronkainen J, Heiskala A, Vehmeijer FOL, Lowry E, Caramaschi D, Estrada Gutiérrez G, Heiss JA, Hummel N, Keikkala E, Kvist T, Kupsco A, Melton PE, Pesce G, Soomro MH, Vives-Usano M, Baiz N, Binder E, Czamara D, Guxens M, Mustaniemi S, London SJ, Rauschert S, Vääräsmäki M, Vrijheid M, Ziegler A-G, Annesi-Maesano I, Bustamante M, Huang R-C, Hummel S, Just AC, Kajantie E, Lahti J, Lawlor D, Räikkönen K, Järvelin M-R, Felix JF, Sebert Set al., 2022, Maternal haemoglobin levels in pregnancy and child DNA methylation: a study in the pregnancy and childhood epigenetics consortium, Epigenetics, Vol: 17, Pages: 19-31, ISSN: 1559-2294

Altered maternal haemoglobin levels during pregnancy are associated with pre-clinical and clinical conditions affecting the fetus. Evidence from animal models suggests that these associations may be partially explained by differential DNA methylation in the newborn with possible long-term consequences. To test this in humans, we meta-analysed the epigenome-wide associations of maternal haemoglobin levels during pregnancy with offspring DNA methylation in 3,967 newborn cord blood and 1,534 child and 1,962 adolescent whole-blood samples derived from ten cohorts. DNA methylation was measured using Illumina Infinium Methylation450K or MethylationEPIC arrays covering 450,000 and 850,000 methylation sites, respectively. There was no statistical support for association of maternal haemoglobin levels with offspring DNA methylation either at individual methylation sites or clustered in regions. For most participants, maternal haemoglobin levels were within the normal range in the current study, whereas adverse perinatal outcomes often arise at the extremes. Thus, this study does not rule out the possibility that associations with offspring DNA methylation might be seen in studies with more extreme maternal haemoglobin levels.

Journal article

Jarvelin M-R, Wielscher M, Amaral AF, van der Plaat D, Wain LV, Sebert S, Mosen-Ansorena D, Auvinen J, Herzig K-H, Dehghan A, Jarvis DLet al., 2021, Genetic correlation and causal relationships between cardio-metabolic traits and lung function impairment, Genome Medicine, Vol: 13, Pages: 1-13, ISSN: 1756-994X

AbstractBackground: Associations of low lung function with features of poor cardio-metabolic health have been reported.It is, however, unclear whether these co-morbidities reflect causal associations, shared genetic heritability or areconfounded by environmental factors.Methods: We performed three analyses: (1) cardio-metabolic health to lung function association tests in NorthernFinland Birth cohort 1966, (2) cross-trait linkage disequilibrium score regression (LDSC) to compare geneticbackgrounds and (3) Mendelian randomisation (MR) analysis to assess the causal effect of cardio-metabolic traitsand disease on lung function, and vice versa (bidirectional MR). Genetic associations were obtained from the UKBiobank data or published large-scale genome-wide association studies (N > 82,000).Results: We observed a negative genetic correlation between lung function and cardio-metabolic traits and diseases.In Mendelian Randomisation analysis (MR), we found associations between type 2 diabetes (T2D) instruments andforced vital capacity (FVC) as well as FEV1/FVC. Body mass index (BMI) instruments were associated to all lung functiontraits and C-reactive protein (CRP) instruments to FVC. These genetic associations provide evidence for a causal effectof cardio-metabolic traits on lung function. Multivariable MR suggested independence of these causal effects fromother tested cardio-metabolic traits and diseases. Analysis of lung function specific SNPs revealed a potential causaleffect of FEV1/FVC on blood pressure.Conclusions: The present study overcomes many limitations of observational studies by using MendelianRandomisation. We provide evidence for an independent causal effect of T2D, CRP and BMI on lung functionwith some of the T2D effect on lung function being attributed to inflammatory mechanisms. Furthermore,this analysis suggests a potential causal effect of FEV1/FVC on blood pressure. Our detailed analysis of theinterplay between cardio-metabolic traits and impaired

Journal article

Miller BJ, Herzig K-H, Jokelainen J, Karhu T, Keinanen-Kiukaanniemi S, Jarvelin M-R, Veijola J, Viinamaki H, Tanskanen P, Jaaskelainen E, Isohanni M, Timonen Met al., 2021, Inflammation, hippocampal volume, and cognition in schizophrenia: results from the Northern Finland Birth Cohort 1966, EUROPEAN ARCHIVES OF PSYCHIATRY AND CLINICAL NEUROSCIENCE, Vol: 271, Pages: 609-622, ISSN: 0940-1334

Journal article

Robinson O, Carter AR, Aola-Korpela M, Casas JP, Chaturvedi N, Engmann J, Howe LD, Hughes A, Jarvelin MJ, Kahonen M, Karhunen V, Kuh D, Shah T, Ben-Shlomo Y, Sofat R, Lau CE, Lehtimaki T, Menon U, Raitakari O, Ryan A, Providencia R, Smith S, Taylor J, Tillin T, Viikari J, Wong A, Hingorani AD, Kivimaki M, Vineis Pet al., 2021, Metabolic profiles of socioeconomic position: a multi-cohort analysis, International Journal of Epidemiology, Vol: 50, Pages: 768-782, ISSN: 0300-5771

BackgroundLow socioeconomic position (SEP) is a risk factor for multiple health outcomes, but its molecular imprints in the body remain unclear. MethodsWe examined SEP as a determinant of serum nuclear magnetic resonance metabolic profiles, in approximately 30,000 adults and 4,000 children across ten UK and Finnish cohort studies. ResultsIn risk factor-adjusted analysis of 233 metabolic measures, low educational attainment was associated with 37 measures including higher levels of triglycerides in small high-density lipoproteins (HDL) and lower levels of docosahexaenoic acid (DHA), omega-3 fatty acids, apolipoprotein A1, large and very large HDL particles (including levels of their respective lipid constituents), and cholesterol measures across different density lipoproteins. Among adults whose father worked in manual occupations, associations with apolipoprotein A1, large and very large HDL particles and HDL-2 cholesterol remained after adjustment for SEP in later life. Among manual workers, levels of glutamine were higher compared to non-manual workers. All three indicators of low SEP were associated with lower DHA, omega-3 fatty acids and HDL diameter. At all ages, children of manual workers had lower levels of DHA as a proportion of total fatty acids.ConclusionsOur work indicates that social and economic factors have a measurable impact on human physiology. Lower SEP was independently associated with a generally unfavorable metabolic profile, consistent across ages and cohorts. The metabolites we found associated with SEP, including DHA, are known to predict cardiovascular disease and cognitive decline in later life and may contribute to health inequalities.

Journal article

Wang Q, Oliver-Williams C, Raitakari OT, Viikari J, Lehtimäki T, Kähönen M, Järvelin M-R, Salomaa V, Perola M, Danesh J, Kettunen J, Butterworth AS, Holmes MV, Ala-Korpela Met al., 2021, Metabolic profiling of angiopoietin-like protein 3 and 4 inhibition: a drug-target Mendelian randomization analysis, European Heart Journal, Vol: 42, Pages: 1160-1169, ISSN: 0195-668X

AIMS : Angiopoietin-like protein 3 (ANGPTL3) and 4 (ANGPTL4) inhibit lipoprotein lipase (LPL) and represent emerging drug targets to lower circulating triglycerides and reduce cardiovascular risk. To investigate the molecular effects of genetic mimicry of ANGPTL3 and ANGPTL4 inhibition and compare them to the effects of genetic mimicry of LPL enhancement. METHODS AND RESULTS : Associations of genetic variants in ANGPTL3 (rs11207977-T), ANGPTL4 (rs116843064-A), and LPL (rs115849089-A) with an extensive serum lipid and metabolite profile (208 measures) were characterized in six cohorts of up to 61 240 participants. Genetic associations with anthropometric measures, glucose-insulin metabolism, blood pressure, markers of kidney function, and cardiometabolic endpoints via genome-wide summary data were also explored. ANGPTL4 rs116843064-A and LPL rs115849089-A displayed a strikingly similar pattern of associations across the lipoprotein and lipid measures. However, the corresponding associations with ANGPTL3 rs11207977-T differed, including those for low-density lipoprotein and high-density lipoprotein particle concentrations and compositions. All three genotypes associated with lower concentrations of an inflammatory biomarker glycoprotein acetyls and genetic mimicry of ANGPTL3 inhibition and LPL enhancement were also associated with lower C-reactive protein. Genetic mimicry of ANGPTL4 inhibition and LPL enhancement were associated with a lower waist-to-hip ratio, improved insulin-glucose metabolism, and lower risk of coronary heart disease and type 2 diabetes, whilst genetic mimicry of ANGPTL3 was associated with improved kidney function. CONCLUSIONS : Genetic mimicry of ANGPTL4 inhibition and LPL enhancement have very similar systemic metabolic effects, whereas genetic mimicry of ANGPTL3 inhibition showed differing metabolic effects, suggesting potential involvement of pathways independent of LPL. Genetic mimicry of ANGPTL4 inhibition and LPL enhanc

Journal article

Nedelec R, Miettunen J, Mannikko M, Jarvelin M-R, Sebert Set al., 2021, Maternal and infant prediction of the child BMI trajectories; studies across two generations of Northern Finland birth cohorts, International Journal of Obesity, Vol: 45, Pages: 404-414, ISSN: 0307-0565

Background/objectiveChildren BMI is a longitudinal phenotype, developing through interplays between genetic and environmental factors. Whilst childhood obesity is escalating, we require a better understanding of its early origins and variation across generations to prevent it.Subjects/methodsWe designed a cross-cohort study including 12,040 Finnish children from the Northern Finland Birth Cohorts 1966 and 1986 (NFBC1966 and NFBC1986) born before or at the start of the obesity epidemic. We used group-based trajectory modelling to identify BMI trajectories from 2 to 20 years. We subsequently tested their associations with early determinants (mother and child) and the possible difference between generations, adjusted for relevant biological and socioeconomic confounders.ResultsWe identified four BMI trajectories, ‘stable-low’ (34.8%), ‘normal’ (44.0%), ‘stable-high’ (17.5%) and ‘early-increase’ (3.7%). The ‘early-increase’ trajectory represented the highest risk for obesity. We analysed a dose-response association of maternal pre-pregnancy BMI and smoking with BMI trajectories. The directions of effect were consistent across generations and the effect sizes tended to increase from earlier generation to later. Respectively for NFBC1966 and NFBC1986, the adjusted risk ratios of being in the early-increase group were 1.08 (1.06–1.10) and 1.12 (1.09–1.15) per unit of pre-pregnancy BMI and 1.44 (1.05–1.96) and 1.48 (1.17–1.87) in offspring of smoking mothers compared to non-smokers. We observed similar relations with infant factors including birthweight for gestational age and peak weight velocity. In contrast, the age at adiposity peak in infancy was associated with the BMI trajectories in NFBC1966 but did not replicate in NFBC1986.ConclusionsExposures to adverse maternal predictors were associated with a higher risk obesity trajectory and were consistent across generations. However, we fou

Journal article

Suikkanen J, Miettola S, Heinonen K, Vaarasmaki M, Tikanmaki M, Sipola M, Matinolli H-M, Jarvelin M-R, Raikkonen K, Hovi P, Kajantie Eet al., 2021, Reaction times, learning, and executive functioning in adults born preterm, PEDIATRIC RESEARCH, Vol: 89, Pages: 198-204, ISSN: 0031-3998

Journal article

Nuotio M-L, Pervjakova N, Joensuu A, Karhunen V, Hiekkalinna T, Milani L, Kettunen J, Jarvelin M-R, Jousilahti P, Metspalu A, Salomaa V, Kristiansson K, Perola Met al., 2020, An epigenome-wide association study of metabolic syndrome and its components, Scientific Reports, Vol: 10, Pages: 1-12, ISSN: 2045-2322

The role of metabolic syndrome (MetS) as a preceding metabolic state for type 2 diabetes and cardiovascular disease is widely recognised. To accumulate knowledge of the pathological mechanisms behind the condition at the methylation level, we conducted an epigenome-wide association study (EWAS) of MetS and its components, testing 1187 individuals of European ancestry for approximately 470 000 methylation sites throughout the genome. Methylation site cg19693031 in gene TXNIP —previously associated with type 2 diabetes, glucose and lipid metabolism, associated with fasting glucose level (P = 1.80 × 10−8). Cg06500161 in gene ABCG1 associated both with serum triglycerides (P = 5.36 × 10−9) and waist circumference (P = 5.21 × 10−9). The previously identified type 2 diabetes–associated locus cg08309687 in chromosome 21 associated with waist circumference for the first time (P = 2.24 × 10−7). Furthermore, a novel HDL association with cg17901584 in chromosome 1 was identified (P = 7.81 × 10−8). Our study supports previous genetic studies of MetS, finding that lipid metabolism plays a key role in pathology of the syndrome. We provide evidence regarding a close interplay with glucose metabolism. Finally, we suggest that in attempts to identify methylation loci linking separate MetS components, cg19693031 appears to represent a strong candidate.

Journal article

Vehmeijer FOL, Kuepers LK, Sharp GC, Salas LA, Lent S, Jima DD, Tindula G, Reese S, Qi C, Gruzieva O, Page C, Rezwan F, Melton PE, Nohr E, Escaramis G, Rzehak P, Heiskala A, Gong T, Tuominen ST, Gao L, Ross JP, Starling AP, Holloway JW, Yousefi P, Aasvang GM, Beilin LJ, Bergstrom A, Binder E, Chatzi L, Corpeleijn E, Czamara D, Eskenazi B, Ewart S, Ferre N, Grote V, Gruszfeld D, Haberg SE, Hoyo C, Huen K, Karlsson R, Kull I, Langhendries J-P, Lepeule J, Magnus MC, Maguire RL, Molloy PL, Monnereau C, Mori TA, Oken E, Raikkonen K, Rifas-Shiman S, Ruiz-Arenas C, Sebert S, Ullemar V, Verduci E, Vonk JM, Xu C-J, Yang I, Zhang H, Zhang W, Karmaus W, Dabelea D, Muhlhausler BS, Breton C, Lahti J, Almqvist C, Jarvelin M-R, Koletzko B, Vrijheid M, Sorensen TIA, Huang R-C, Arshad SH, Nystad W, Melen E, Koppelman GH, London SJ, Holland N, Bustamante M, Murphy SK, Hivert M-F, Baccarelli A, Relton CL, Snieder H, Jaddoe VWV, Felix JFet al., 2020, DNA methylation and body mass index from birth to adolescence: meta-analyses of epigenome-wide association studies, Genome Medicine: medicine in the post-genomic era, Vol: 12, Pages: 1-15, ISSN: 1756-994X

BackgroundDNA methylation has been shown to be associated with adiposity in adulthood. However, whether similar DNA methylation patterns are associated with childhood and adolescent body mass index (BMI) is largely unknown. More insight into this relationship at younger ages may have implications for future prevention of obesity and its related traits.MethodsWe examined whether DNA methylation in cord blood and whole blood in childhood and adolescence was associated with BMI in the age range from 2 to 18 years using both cross-sectional and longitudinal models. We performed meta-analyses of epigenome-wide association studies including up to 4133 children from 23 studies. We examined the overlap of findings reported in previous studies in children and adults with those in our analyses and calculated enrichment.ResultsDNA methylation at three CpGs (cg05937453, cg25212453, and cg10040131), each in a different age range, was associated with BMI at Bonferroni significance, P < 1.06 × 10−7, with a 0.96 standard deviation score (SDS) (standard error (SE) 0.17), 0.32 SDS (SE 0.06), and 0.32 BMI SDS (SE 0.06) higher BMI per 10% increase in methylation, respectively. DNA methylation at nine additional CpGs in the cross-sectional childhood model was associated with BMI at false discovery rate significance. The strength of the associations of DNA methylation at the 187 CpGs previously identified to be associated with adult BMI, increased with advancing age across childhood and adolescence in our analyses. In addition, correlation coefficients between effect estimates for those CpGs in adults and in children and adolescents also increased. Among the top findings for each age range, we observed increasing enrichment for the CpGs that were previously identified in adults (birth Penrichment = 1; childhood Penrichment = 2.00 × 10−4; adolescence Penrichment = 2.10&thi

Journal article

Beaumont RN, Kotecha SJ, Wood AR, Knight BA, Sebert S, McCarthy M, Hattersley AT, Jarvelin M-R, Timpson NJ, Freathy RM, Kotecha Set al., 2020, Common maternal and fetal genetic variants show expected polygenic effects on risk of small- or large-for-gestational-age (SGA or LGA), except in the smallest 3% of babies, PLoS Genetics, Vol: 16, Pages: 1-15, ISSN: 1553-7390

Babies born clinically Small- or Large-for-Gestational-Age (SGA or LGA; sex- and gestational age-adjusted birth weight (BW) <10th or >90th percentile, respectively), are at higher risks of complications. SGA and LGA include babies who have experienced environment-related growth-restriction or overgrowth, respectively, and babies who are heritably small or large. However, the relative proportions within each group are unclear. We assessed the extent to which common genetic variants underlying variation in birth weight influence the probability of being SGA or LGA. We calculated independent fetal and maternal genetic scores (GS) for BW in 11,951 babies and 5,182 mothers. These scores capture the direct fetal and indirect maternal (via intrauterine environment) genetic contributions to BW, respectively. We also calculated maternal fasting glucose (FG) and systolic blood pressure (SBP) GS. We tested associations between each GS and probability of SGA or LGA. For the BW GS, we used simulations to assess evidence of deviation from an expected polygenic model.Higher BW GS were strongly associated with lower odds of SGA and higher odds of LGA (ORfetal = 0.75 (0.71,0.80) and 1.32 (1.26,1.39); ORmaternal = 0.81 (0.75,0.88) and 1.17 (1.09,1.25), respectively per 1 decile higher GS). We found evidence that the smallest 3% of babies had a higher BW GS, on average, than expected from their observed birth weight (assuming an additive polygenic model: Pfetal = 0.014, Pmaternal = 0.062). Higher maternal SBP GS was associated with higher odds of SGA P = 0.005.We conclude that common genetic variants contribute to risk of SGA and LGA, but that additional factors become more important for risk of SGA in the smallest 3% of babies.

Journal article

Protsenko M, Kerkelä M, Miettunen J, Auvinen J, Järvelin M-R, Gissler M, Veijola Jet al., 2020, Mortality by diseases and medical conditions in the offspring of parents with severe mental illness., Soc Psychiatry Psychiatr Epidemiol, Vol: 55, Pages: 1649-1657

PURPOSE: The lifespan of people with severe mental illness (SMI) is shorter compared to the general population. There might be common familial pathway leading to a high co-occurrence of somatic disorders and SMI. To study this we explored the long-term mortality for natural causes in the offspring of people with SMI. METHODS: Participants were members of the Northern Finland Birth Cohort 1966 (NFBC1966; N = 11,325). The data on cause of deaths of the members were obtained from the Population Register Center until year 2015. The data on hospital-treated psychiatric disorders of parents were obtained from nationwide Care Register for Health Care. Cumulative incidences by age were calculated in the NFBC1966 members having a parent with SMI and those who did not have. We were able to take into account multiple confounders. RESULTS: Of the total sample of 11,325 offspring, 853 (7.4%) died during the follow-up period, 74 (8.7%) from the study cohort and 779 (91.3%) from the comparison group. These numbers included 160 stillborn children. There were 557 cases of deaths from diseases and medical conditions and 296 deaths from external causes. The adjusted risk ratio for offspring of mothers with SMI was 1.08 (0.72-1.64), and for offspring of fathers with SMI 0.58 (0.36-0.93). CONCLUSIONS: This was the first long-term follow-up study (up to age 49) of all-cause mortality in offspring of parents with SMI. Our findings were contrary to expectations. Offspring of parents with SMI had no increased risk for dying. In fact, the risk for dying in the group of offspring of fathers with SMI was lower than in the comparison group. This study does not support the assumption of common familial pathway leading to a high co-occurrence of somatic disorders and SMI.

Journal article

Surendran P, Gao H, Zhang W, Evangelou E, Poulter N, Sever PJ, Vergnaud A, Chambers JC, Elliott P, Jarvelin M-R, Kooner JS, Howson Jet al., 2020, Discovery of rare variants associated with blood pressure regulation trhough meta-analaysis of 1.3 million individuals, Nature Genetics, Vol: 52, Pages: 1314-1332, ISSN: 1061-4036

Genetic studies of blood pressure (BP) to date have mainly analyzed common variants (minor allele frequency, MAF > 0.05). In a meta-analysis of up to >1.3 million participants, we discovered 106 new BP-associated genomic regions and 87 rare (MAF≤ 0.01) variant BP associations (P < 5 × 10-8), of which 32 were in new BP-associated loci and 55 were independent BP-associated SNVs within known BP-associated regions. Average effects of rare variants (44% coding) were ~8 times larger than common variant effects and indicate potential candidate causal genes at new and known loci (e.g.GATA5, PLCB3). BP-associated variants (including rare and common) were enriched in regions of active chromatin in fetal tissues, potentially linking fetal development with BP regulation in later life. Multivariable Mendelian randomization suggested possible inverse effects of elevated systolic and diastolic BP on large artery stroke. Our study demonstrates the utility of rare variant analyses for identifying candidate genes and the results highlight potential therapeutic targets.

Journal article

Rodriguez-Martinez A, Zhou B, Sophiea MK, Bentham J, Paciorek CJ, Iurilli ML, Carrillo-Larco RM, Bennett JE, Di Cesare M, Taddei C, Bixby H, Stevens GA, Riley LM, Cowan MJ, Savin S, Danaei G, Chirita-Emandi A, Kengne AP, Khang YH, Laxmaiah A, Malekzadeh R, Miranda JJ, Moon JS, Popovic SR, Sørensen TI, Soric M, Starc G, Zainuddin AA, Gregg EW, Bhutta ZA, Black R, Abarca-Gómez L, Abdeen ZA, Abdrakhmanova S, Abdul Ghaffar S, Abdul Rahim HF, Abu-Rmeileh NM, Abubakar Garba J, Acosta-Cazares B, Adams RJ, Aekplakorn W, Afsana K, Afzal S, Agdeppa IA, Aghazadeh-Attari J, Aguilar-Salinas CA, Agyemang C, Ahmad MH, Ahmad NA, Ahmadi A, Ahmadi N, Ahmed SH, Ahrens W, Aitmurzaeva G, Ajlouni K, Al-Hazzaa HM, Al-Othman AR, Al-Raddadi R, Alarouj M, AlBuhairan F, AlDhukair S, Ali MM, Alkandari A, Alkerwi A, Allin K, Alvarez-Pedrerol M, Aly E, Amarapurkar DN, Amiri P, Amougou N, Amouyel P, Andersen LB, Anderssen SA, Ängquist L, Anjana RM, Ansari-Moghaddam A, Aounallah-Skhiri H, Araújo J, Ariansen I, Aris T, Arku RE, Arlappa N, Aryal KK, Aspelund T, Assah FK, Assunção MCF, Aung MS, Auvinen J, Avdicová M, Azevedo A, Azimi-Nezhad M, Azizi F, Azmin M, Babu BV, Bæksgaard Jørgensen M, Baharudin A, Bahijri S, Baker JL, Balakrishna N, Bamoshmoosh Met al., 2020, Height and body-mass index trajectories of school-aged children and adolescents from 1985 to 2019 in 200 countries and territories: a pooled analysis of 2181 population-based studies with 65 million participants, The Lancet, Vol: 396, Pages: 1511-1524, ISSN: 0140-6736

SummaryBackgroundComparable global data on health and nutrition of school-aged children and adolescents are scarce. We aimed to estimate age trajectories and time trends in mean height and mean body-mass index (BMI), which measures weight gain beyond what is expected from height gain, for school-aged children and adolescents.MethodsFor this pooled analysis, we used a database of cardiometabolic risk factors collated by the Non-Communicable Disease Risk Factor Collaboration. We applied a Bayesian hierarchical model to estimate trends from 1985 to 2019 in mean height and mean BMI in 1-year age groups for ages 5–19 years. The model allowed for non-linear changes over time in mean height and mean BMI and for non-linear changes with age of children and adolescents, including periods of rapid growth during adolescence.FindingsWe pooled data from 2181 population-based studies, with measurements of height and weight in 65 million participants in 200 countries and territories. In 2019, we estimated a difference of 20 cm or higher in mean height of 19-year-old adolescents between countries with the tallest populations (the Netherlands, Montenegro, Estonia, and Bosnia and Herzegovina for boys; and the Netherlands, Montenegro, Denmark, and Iceland for girls) and those with the shortest populations (Timor-Leste, Laos, Solomon Islands, and Papua New Guinea for boys; and Guatemala, Bangladesh, Nepal, and Timor-Leste for girls). In the same year, the difference between the highest mean BMI (in Pacific island countries, Kuwait, Bahrain, The Bahamas, Chile, the USA, and New Zealand for both boys and girls and in South Africa for girls) and lowest mean BMI (in India, Bangladesh, Timor-Leste, Ethiopia, and Chad for boys and girls; and in Japan and Romania for girls) was approximately 9–10 kg/m2. In some countries, children aged 5 years started with healthier height or BMI than the global median and, in some cases, as healthy as the best performing countries, but they became

Journal article

Loftfield E, Herzig K-H, Caporaso JG, Derkach A, Wan Y, Byrd DA, Vogtmann E, Mannikko MM, Karhunen V, Knight R, Gunter MJ, Jarvelin M-R, Sinha Ret al., 2020, Association of body mass index with fecal microbial diversity and metabolites in the northern Finland birth cohort, Cancer Epidemiology, Biomarkers and Prevention, Vol: 29, Pages: 2289-2299, ISSN: 1055-9965

Background: Obesity is an established risk factor for multiple cancer types. Lower microbial richness has been linked to obesity, but human studies are inconsistent, and associations of early-life body mass index (BMI) with the fecal microbiome and metabolome are unknown.Methods: We characterized the fecal microbiome (n = 563) and metabolome (n = 340) in the Northern Finland Birth Cohort 1966 using 16S rRNA gene sequencing and untargeted metabolomics. We estimated associations of adult BMI and BMI history with microbial features and metabolites using linear regression and Spearman correlations (rs) and computed correlations between bacterial sequence variants and metabolites overall and by BMI category.Results: Microbial richness, including the number of sequence variants (rs = −0.21, P < 0.0001), decreased with increasing adult BMI but was not independently associated with BMI history. Adult BMI was associated with 56 metabolites but no bacterial genera. Significant correlations were observed between microbes in 5 bacterial phyla, including 18 bacterial genera, and metabolites in 49 of the 62 metabolic pathways evaluated. The genera with the strongest correlations with relative metabolite levels (positively and negatively) were Blautia, Oscillospira, and Ruminococcus in the Firmicutes phylum, but associations varied by adult BMI category.Conclusions: BMI is strongly related to fecal metabolite levels, and numerous associations between fecal microbial features and metabolite levels underscore the dynamic role of the gut microbiota in metabolism.Impact: Characterizing the associations between the fecal microbiome, the fecal metabolome, and BMI, both recent and early-life exposures, provides critical background information for future research on cancer prevention and etiology.

Journal article

Parmar P, Lowry E, Vehmeijer F, El Marroun H, Lewin A, Tolvanen M, Tzala E, Ala-Mursula L, Herzig K-H, Miettunen J, Prokopenko I, Rautio N, Jaddoe VWV, Jarvelin M-R, Felix J, Sebert Set al., 2020, Understanding the cumulative risk of maternal prenatal biopsychosocial factors on birth weight: a DynaHEALTH study on two birth cohorts, Journal of Epidemiology and Community Health, Vol: 74, Pages: 933-941, ISSN: 0143-005X

Background There are various maternal prenatal biopsychosocial (BPS) predictors of birth weight, making it difficult to quantify their cumulative relationship.Methods We studied two birth cohorts: Northern Finland Birth Cohort 1986 (NFBC1986) born in 1985–1986 and the Generation R Study (from the Netherlands) born in 2002–2006. In NFBC1986, we selected variables depicting BPS exposure in association with birth weight and performed factor analysis to derive latent constructs representing the relationship between these variables. In Generation R, the same factors were generated weighted by loadings of NFBC1986. Factor scores from each factor were then allocated into tertiles and added together to calculate a cumulative BPS score. In all cases, we used regression analyses to explore the relationship with birth weight corrected for sex and gestational age and additionally adjusted for other factors.Results Factor analysis supported a four-factor structure, labelled closely to represent their characteristics as ‘Factor1-BMI’ (body mass index), ‘Factor2-DBP’ (diastolic blood pressure), ‘Factor3-Socioeconomic-Obstetric-Profile’ and ‘Factor4-Parental-Lifestyle’. In both cohorts, ‘Factor1-BMI’ was positively associated with birth weight, whereas other factors showed negative association. ‘Factor3-Socioeconomic-Obstetric-Profile’ and ‘Factor4-Parental-Lifestyle’ had the greatest effect size, explaining 30% of the variation in birth weight. Associations of the factors with birth weight were largely driven by ‘Factor1-BMI’. Graded decrease in birth weight was observed with increasing cumulative BPS score, jointly evaluating four factors in both cohorts.Conclusion Our study is a proof of concept for maternal prenatal BPS hypothesis, highlighting the components snowball effect on birth weight in two different European birth cohorts.

Journal article

van Dongen J, Hagenbeek FA, Suderman M, Roetman P, Sugden K, Chiocchetti AG, Ismail K, Mulder RH, Hafferty J, Adams MJ, Walker RM, Morris SW, Lahti J, Kupers LK, Escaramis G, Alemany S, Bonder MJ, Meijer M, Ip HF, Jansen R, Baselmans BML, Parmar P, Lowry E, Streit F, Sirignano L, Send T, Frank J, Jylhava J, Wang Y, Mishra PP, Colins OF, Corcoran D, Poulton R, Mill J, Hannon EJ, Arseneault L, Korhonen T, Vuoksimaa E, Felix J, Bakermans-Kranenburg M, Campbell A, Czamara D, Binder E, Corpeleijn E, Ramon Gonzalez J, Grazuleviciene R, Gutzkow KB, Evandt J, Vafeiadi M, Klein M, van der Meer D, Ligthart L, Kluft C, Davies GE, Hakulinen C, Keltikangas-Jarvinen L, Franke B, Freitag CM, Konrad K, Hervas A, Fernandez-Rivas A, Vetro A, Raitakari O, Lehtimaki T, Vermeiren R, Strandberg T, Raikkonen K, Snieder H, Witt SH, Deuschle M, Pedersen NL, Hagg S, Sunyer J, Franke L, Kaprio J, Ollikainen M, Moffitt TE, Tiemeier H, van Ijzendoorn MH, Relton C, Vrijheid M, Sebert S, Jarvelin M-R, Caspi A, Evans KL, McIntosh AM, Bartels M, Boomsma Det al., 2020, DNA methylation signatures of a broad spectrum of aggressive behavior: a meta-analysis of epigenome-wide studies across the lifespan, 50th Annual Meeting of the Behavior-Genetics-Association (BGA), Publisher: Springer, Pages: 485-487, ISSN: 0001-8244

Conference paper

West S, Ollila M-M, Franks S, Piltonen T, Jokelainen J, Nevalainen J, Puukka K, Ruokonen A, Jarvelin M-R, Auvinen J, Tapanainen JS, Morin-Papunen Let al., 2020, Overweight, obesity and hyperandrogenemia are associated with gestational diabetes mellitus: A follow-up cohort study, Acta Obstetricia et Gynecologica Scandinavica, Vol: 99, Pages: 1311-1319, ISSN: 0001-6349

IntroductionThe aim of the study was to determine the association of body mass index (BMI), self‐reported symptoms or diagnosis of polycystic ovary syndrome (PCOS), and hyperandrogenemia with the occurrence of gestational diabetes mellitus (GDM) through reproductive life.Material and methodsA cohort of women born in 1966 were investigated at ages 14, 31 and 46. Women with self‐reported PCOS symptoms (presence of both oligo‐amenorrhea and hirsutism) at age 31 or with formally diagnosed polycystic ovaries (PCO)/PCOS by age 46 formed the group of self‐reported PCOS (srPCOS, n = 222) and were compared with women without self‐reported PCOS symptoms or diagnosis (n = 1357). We investigated also the association of hyperandrogenism (hirsutism or biochemical hyperandrogenism) at age 31 with the occurrence of GDM throughout reproductive life.ResultsSelf‐reported PCOS alone was not a risk factor for GDM, but combined with overweight at age 31 (odds ratio [OR] 2.43, 95% confidence interval [CI] 1.22‐4.86) or 46 (OR 3.04, 95% CI 1.58‐5.83) srPCOS was associated with GDM when compared with normal weight controls. The association disappeared when comparing overweight srPCOS women with overweight controls. However, hyperandrogenemia at age 31, but not hirsutism, was associated with GDM even after adjustment for BMI.ConclusionsThe increased risk of GDM in women with srPCOS was mostly attributed to overweight or obesity. Importantly, normal weight women with srPCOS did not seem to be at increased risk for developing GDM. However, hyperandrogenemia was associated with GDM even after adjustment for BMI. These findings strengthen the importance of weight management in reproductive‐age women and suggest a noteworthy role of hyperandrogenemia in the pathophysiology of GDM.

Journal article

Vogelezang S, Bradfield JP, Ahluwalia TS, Curtin JA, Lakka TA, Grarup N, Scholz M, van der Most PJ, Monnereau C, Stergiakouli E, Heiskala A, Horikoshi M, Fedko IO, Vilor-Tejedor N, Cousminer DL, Standl M, Wang CA, Viikari J, Geller F, iniguez C, Pitkanen N, Chesi A, Bacelis J, Yengo L, Torrent M, Ntalla I, Helgeland O, Selzam S, Vonk JM, Zafarmand MH, Heude B, Farooqi IS, Alyass A, Beaumont RN, Have CT, Rzehak P, Bilbao JR, Schnurr TM, Barroso I, Bonnelykke K, Beilin LJ, Carstensen L, Charles M-A, Chawes B, Clement K, Closa-Monasterolo R, Custovic A, Eriksson JG, Escribano J, Groen-Blokhuis M, Grote V, Gruszfeld D, Hakonarson H, Hansen T, Hattersley AT, Hollensted M, Hottenga J-J, Hypponen E, Johansson S, Joro R, Kahonen M, Karhunen V, Kiess W, Knight BA, Koletzko B, Kuehnapfel A, Landgraf K, Langhendries J-P, Lehtimaki T, Leinonen JT, Li A, Lindi V, Lowry E, Bustamante M, Medina-Gomez C, Melbye M, Michaelsen KF, Morgen CS, Mori TA, Nielsen TRH, Niinikoski H, Oldehinkel AJ, Pahkala K, Panoutsopoulou K, Pedersen O, Pennell CE, Power C, Reijneveld SA, Rivadeneira F, Simpson A, Sly PD, Stokholm J, Teo KK, Thiering E, Timpson NJ, Uitterlinden AG, van Beijsterveldt CEM, van Schaik BDC, Vaudel M, Verduci E, Vinding RK, Vogel M, Zeggini E, Sebert S, Lind MV, Brown CD, Santa-Marina L, Reischl E, Frithioff-Bojsoe C, Meyre D, Wheeler E, Ong K, Nohr EA, Vrijkotte TGM, Koppelman GH, Plomin R, Njolstad PR, Dedoussis GD, Froguel P, Sorensen TIA, Jacobsson B, Freathy RM, Zemel BS, Raitakari O, Vrijheid M, Feenstra B, Lyytikainen L-P, Snieder H, Kirsten H, Holt PG, Heinrich J, Widen E, Sunyer J, Boomsma DI, Jarvelin M-R, Koerner A, Davey Smith G, Holm J-C, Atalay M, Murray C, Bisgaard H, McCarthy MI, Jaddoe VWV, Grant SFA, Felix JFet al., 2020, Novel loci for childhood body mass index and shared heritability with adult cardiometabolic traits, PLoS Genetics, Vol: 16, Pages: 1-26, ISSN: 1553-7390

The genetic background of childhood body mass index (BMI), and the extent to which the well-known associations of childhood BMI with adult diseases are explained by shared genetic factors, are largely unknown. We performed a genome-wide association study meta-analysis of BMI in 61,111 children aged between 2 and 10 years. Twenty-five independent loci reached genome-wide significance in the combined discovery and replication analyses. Two of these, located near NEDD4L and SLC45A3, have not previously been reported in relation to either childhood or adult BMI. Positive genetic correlations of childhood BMI with birth weight and adult BMI, waist-to-hip ratio, diastolic blood pressure and type 2 diabetes were detected (Rg ranging from 0.11 to 0.76, P-values <0.002). A negative genetic correlation of childhood BMI with age at menarche was observed. Our results suggest that the biological processes underlying childhood BMI largely, but not completely, overlap with those underlying adult BMI. The well-known observational associations of BMI in childhood with cardio-metabolic diseases in adulthood may reflect partial genetic overlap, but in light of previous evidence, it is also likely that they are explained through phenotypic continuity of BMI from childhood into adulthood.

Journal article

Rauschert S, Melton PE, Heiskala A, Karhunen V, Burdge G, Craig JM, Godfrey KM, Lillycrop K, Mori TA, Beilin LJ, Oddy WH, Pennell C, Jarvelin M-R, Sebert S, Huang R-Cet al., 2020, Machine learning-based DNA methylation score for fetal exposure to maternal smoking: development and validation in samples collected from adolescents and adults, Environmental Health Perspectives, Vol: 128, Pages: 097003-1-097003-11, ISSN: 0091-6765

Background:Fetal exposure to maternal smoking during pregnancy is associated with the development of noncommunicable diseases in the offspring. Maternal smoking may induce such long-term effects through persistent changes in the DNA methylome, which therefore hold the potential to be used as a biomarker of this early life exposure. With declining costs for measuring DNA methylation, we aimed to develop a DNA methylation score that can be used on adolescent DNA methylation data and thereby generate a score for in utero cigarette smoke exposure.Methods:We used machine learning methods to create a score reflecting exposure to maternal smoking during pregnancy. This score is based on peripheral blood measurements of DNA methylation (Illumina’s Infinium HumanMethylation450K BeadChip). The score was developed and tested in the Raine Study with data from 995 white 17-y-old participants using 10-fold cross-validation. The score was further tested and validated in independent data from the Northern Finland Birth Cohort 1986 (NFBC1986) (16-y-olds) and 1966 (NFBC1966) (31-y-olds). Further, three previously proposed DNA methylation scores were applied for comparison. The final score was developed with 204 CpGs using elastic net regression.Results:Sensitivity and specificity values for the best performing previously developed classifier (“Reese Score”) were 88% and 72% for Raine, 87% and 61% for NFBC1986 and 72% and 70% for NFBC1966, respectively; corresponding figures using the elastic net regression approach were 91% and 76% (Raine), 87% and 75% (NFBC1986), and 72% and 78% for NFBC1966.Conclusion:We have developed a DNA methylation score for exposure to maternal smoking during pregnancy, outperforming the three previously developed scores. One possible application of the current score could be for model adjustment purposes or to assess its association with distal health outcomes where part of the effect can be attributed to maternal smoking. Further, it may p

Journal article

Parviainen R, Auvinen J, Serlo W, Jarvelin M-R, Sinikumpu J-Jet al., 2020, Maternal alcohol consumption during pregnancy associates with bone fractures in early childhood. A birth-cohort study of 6718 participants, Bone, Vol: 137, Pages: 1-6, ISSN: 1873-2763

Fractures are common injuries in children, but their underlying biological and environmental risk factors are not well known. Maternal alcohol consumption during pregnancy is a known risk factor for bone malformations and impaired growth, in connection with Fetal Alcohol Spectrum Disorders (FASD). There is evidence that even lower doses of alcohol than what is needed for FASD can cause changes in the developing bone. Birth weight and length may also associate to childhood fractures. The aim of this study was to find out whether there exist associations between maternal alcohol use during pregnancy, birth weight or length and fractures of the long bones in childhood.A prospective birth cohort was performed, including all women in Northern Finland with an expected date of delivery between July 1985 and June 1986, and their offspring (N = 9432). The National Hospital Discharge Register (NHDR) provided the information on inpatient treated fractures. The subjects who declined participation or were treated as outpatient were excluded. The final study population consisted of 6718 children (71.2%). 98 (1.5%) of them suffered from inpatient treated fracture of a long bone (N = 105). Maternal alcohol consumption during pregnancy was inquired by questionnaires during late pregnancy or shortly after parturition. The birth length and weight were recorded immediately after birth.Binomial regression analysis was used to determine the association between the potential explanatory variables and bone fractures. Gender, socioeconomic status of the family, maternal age, premature birth, body mass index (BMI) of the children and maternal smoking during pregnancy were taken as possible confounders.In this study, the maternal alcohol consumption during pregnancy was associated to 2.22-fold (CI 1.09–4.12, p < 0.02) increased risk of a long bone fracture before the age of eight. Birth weight or length did not associate to childhood fractures.Bone fractures are an important cause of

Journal article

Ekholm J, Ohukainen P, Kangas AJ, Kettunen J, Wang Q, Karsikas M, Khan AA, Kingwell BA, Kahonen M, Lehtimaki T, Raitakari OT, Jarvelin M-R, Meikle PJ, Ala-Korpela Met al., 2020, EpiMetal: an open-source graphical web browser tool for easy statistical analyses in epidemiology and metabolomics, International Journal of Epidemiology, Vol: 49, Pages: 1075-1081, ISSN: 0300-5771

MotivationAn intuitive graphical interface that allows statistical analyses and visualizations of extensive data without any knowledge of dedicated statistical software or programming.ImplementationEpiMetal is a single-page web application written in JavaScript, to be used via a modern desktop web browser.General featuresStandard epidemiological analyses and self-organizing maps for data-driven metabolic profiling are included. Multiple extensive datasets with an arbitrary number of continuous and category variables can be integrated with the software. Any snapshot of the analyses can be saved and shared with others via a www-link. We demonstrate the usage of EpiMetal using pilot data with over 500 quantitative molecular measures for each sample as well as in two large-scale epidemiological cohorts (N >10 000).AvailabilityThe software usage exemplar and the pilot data are open access online at [http://EpiMetal.computationalmedicine.fi]. MIT licensed source code is available at the Github repository at [https://github.com/amergin/epimetal].

Journal article

Parra GR, Patwardhan I, Mason WA, Chmelka MB, Savolainen J, Miettunen J, Jarvelin M-Ret al., 2020, Parental Alcohol Use and the Alcohol Misuse of their Offspring in a Finnish Birth Cohort: Investigation of Developmental Timing, JOURNAL OF YOUTH AND ADOLESCENCE, Vol: 49, Pages: 1702-1715, ISSN: 0047-2891

Journal article

Jaddoe VWV, Felix JF, Andersen A-MN, Charles M-A, Chatzi L, Corpeleijn E, Donner N, Elhakeem A, Eriksson JG, Foong R, Grote V, Haakma S, Hanson M, Harris JR, Heude B, Huang R-C, Inskip H, Jarvelin M-R, Koletzko B, Lawlor DA, Lindeboom M, McEachan RRC, Mikkola TM, Nader JLT, de Moira AP, Pizzi C, Richiardi L, Sebert S, Schwalber A, Sunyer J, Swertz MA, Vafeiadi M, Vrijheid M, Wright J, Duijts Let al., 2020, The LifeCycle Project-EU Child Cohort Network: a federated analysis infrastructure and harmonized data of more than 250,000 children and parents, European Journal of Epidemiology, Vol: 35, Pages: 709-724, ISSN: 0393-2990

Early life is an important window of opportunity to improve health across the full lifecycle. An accumulating body of evidence suggests that exposure to adverse stressors during early life leads to developmental adaptations, which subsequently affect disease risk in later life. Also, geographical, socio-economic, and ethnic differences are related to health inequalities from early life onwards. To address these important public health challenges, many European pregnancy and childhood cohorts have been established over the last 30 years. The enormous wealth of data of these cohorts has led to important new biological insights and important impact for health from early life onwards. The impact of these cohorts and their data could be further increased by combining data from different cohorts. Combining data will lead to the possibility of identifying smaller effect estimates, and the opportunity to better identify risk groups and risk factors leading to disease across the lifecycle across countries. Also, it enables research on better causal understanding and modelling of life course health trajectories. The EU Child Cohort Network, established by the Horizon2020-funded LifeCycle Project, brings together nineteen pregnancy and childhood cohorts, together including more than 250,000 children and their parents. A large set of variables has been harmonised and standardized across these cohorts. The harmonized data are kept within each institution and can be accessed by external researchers through a shared federated data analysis platform using the R-based platform DataSHIELD, which takes relevant national and international data regulations into account. The EU Child Cohort Network has an open character. All protocols for data harmonization and setting up the data analysis platform are available online. The EU Child Cohort Network creates great opportunities for researchers to use data from different cohorts, during and beyond the LifeCycle Project duration. It also prov

Journal article

Kaseva N, Vaarasmaki M, Matinolli H-M, Sipola M, Tikanmaki M, Kanerva N, Heinonen K, Lano A, Wolke D, Andersson S, Jarvelin M-R, Raikkonen K, Eriksson JG, Mannisto S, Kajantie Eet al., 2020, Maternal pre-pregnancy overweight and gestational diabetes and dietary intakes among young adult offspring, Nutrition and Diabetes, Vol: 10, Pages: 1-12, ISSN: 2044-4052

Background/ObjectivesMaternal pre-pregnancy overweight/obesity and gestational diabetes (GDM) are associated with increased fat deposition in adult offspring. The purpose of this study was to identify if maternal pre-pregnancy overweight (body mass index (BMI) ≥ 25 kg/m2) or GDM are associated with dietary quality or intake in adult offspring.Subjects/MethodsParticipants (n = 882) from two longitudinal cohort studies (ESTER Maternal Pregnancy Disorders Study and the Arvo Ylppö Longitudinal Study) completed a validated food-frequency questionnaire at a mean age of 24.2 years (SD 1.3). Diet quality was evaluated by a Recommended Finnish Diet Index (RDI). The study sample included offspring of normoglycaemic mothers with pre-pregnancy overweight/obesity (ONO = 155), offspring of mothers with GDM regardless of BMI (OGDM = 190) and offspring of mothers with normal weight and no GDM (controls; n = 537).ResultsAmong men, daily energy and macronutrient intakes were similar in ONO and controls. However, after adjusting for current offspring characteristics, including BMI, daily carbohydrate intake relative to total energy intake was higher in ONO-men [2.2 percentages of total energy intake (95% confidence interval 0.4, 4.0)]. In ONO-women, macronutrient intakes relative to total energy intake were similar with controls, while total daily energy intake seemed lower [−587.2 kJ/day (−1192.0, 4.4)]. After adjusting for confounders, this difference was attenuated. Adherence to a healthy diet, as measured by RDI, was similar in ONO and controls [mean difference: men 0.40 (−0.38, 1.18); women 0.25 (−0.50, 1.00)]. In OGDM vs. controls, total energy and macronutrient intakes were similar for both men and women. Also adherence to a healthy diet was similar [RDI: men 0.09 (−0.62, 0.80); women −0.17 (−0.93, 0.59)].ConclusionsOur study suggested higher dai

Journal article

Akingbuwa WA, Hammerschlag AR, Jami ES, Allegrini AG, Karhunen V, Sallis H, Ask H, Askeland RB, Baselmans B, Diemer E, Hagenbeek FA, Havdahl A, Hottenga J-J, Mbarek H, Rivadeneira F, Tesli M, van Beijsterveldt C, Breen G, Lewis CM, Thapar A, Boomsma DI, Kuja-Halkola R, Reichborn-Kjennerud T, Magnus P, Rimfeld K, Ystrom E, Jarvelin M-R, Lichtenstein P, Lundstrom S, Munafo MR, Plomin R, Tiemeier H, Nivard MG, Bartels M, Middeldorp CMet al., 2020, Genetic associations between childhood psychopathology and adult depression and associated traits in 42998 individuals a meta-analysis, JAMA Psychiatry, Vol: 77, Pages: 715-728, ISSN: 2168-622X

Importance Adult mood disorders are often preceded by behavioral and emotional problems in childhood. It is yet unclear what explains the associations between childhood psychopathology and adult traits.Objective To investigate whether genetic risk for adult mood disorders and associated traits is associated with childhood disorders.Design, Setting, and Participants This meta-analysis examined data from 7 ongoing longitudinal birth and childhood cohorts from the UK, the Netherlands, Sweden, Norway, and Finland. Starting points of data collection ranged from July 1985 to April 2002. Participants were repeatedly assessed for childhood psychopathology from ages 6 to 17 years. Data analysis occurred from September 2017 to May 2019.Exposures Individual polygenic scores (PGS) were constructed in children based on genome-wide association studies of adult major depression, bipolar disorder, subjective well-being, neuroticism, insomnia, educational attainment, and body mass index (BMI).Main Outcomes and Measures Regression meta-analyses were used to test associations between PGS and attention-deficit/hyperactivity disorder (ADHD) symptoms and internalizing and social problems measured repeatedly across childhood and adolescence and whether these associations depended on childhood phenotype, age, and rater.Results The sample included 42 998 participants aged 6 to 17 years. Male participants varied from 43.0% (1040 of 2417 participants) to 53.1% (2434 of 4583 participants) by age and across all cohorts. The PGS of adult major depression, neuroticism, BMI, and insomnia were positively associated with childhood psychopathology (β estimate range, 0.023-0.042 [95% CI, 0.017–0.049]), while associations with PGS of subjective well-being and educational attainment were negative (β, −0.026 to −0.046 [95% CI, −0.020 to −0.057]). There was no moderation of age, type of childhood phenotype, or rater with the associations. The exceptions were s

Journal article

Pupko I, Draisma H, Zudina L, Balkhiyarova Z, Wielscher M, Ala-Korpela M, Sebert S, Jarvelin M-R, Kaakinen M, Prokopenko Iet al., 2020, Epigenome-Wide Association Study of Longitudinal Changes in Blood Metabolite Levels from Young to Middle Adulthood, 48th European Mathematical Genetics Meeting (EMGM), Publisher: KARGER, Pages: 220-221, ISSN: 0001-5652

Conference paper

Kaakinen M, Anasanti M, Jarvelin M-R, Prokopenko Iet al., 2020, ImputeSCOPA: a Fast, Random Forest-Based Phenotype Imputation Tool for Large-Scale Studies, 48th European Mathematical Genetics Meeting (EMGM), Publisher: KARGER, Pages: 212-212, ISSN: 0001-5652

Conference paper

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